Standards for distribution models in biodiversity assessments

By Miguel B. Araújo, R. P. Anderson, A. Barbosa, Colin M. Beale, Carsten F. Dormann, R. Early, R. A. Garcia, Antoine Guisan, Luigi Maiorano, Babak Naimi and 3 more. Science Advances, 2019

988 citations recorded by the source corpus.

Biodiversity assessments use a variety of data and models. We propose best-practice standards for studies in these assessments. Demand for models in biodiversity assessments is rising, but which models are adequate for the task? We propose a set of best-practice standards and detailed guidelines enabling scoring of studies based on species distribution models for use in biodiversity assessments. We reviewed and scored 400 modeling studies over the past 20 years using the proposed standards and guidelines. We detected low model adequacy overall, but with a marked tendency of improvement over time in model building and, to a lesser degree, in biological data and model evaluation. We argue that implementation of agreed-upon standards for models in biodiversity assessments would promote transparency and repeatability, eventually leading to higher quality of the models and the inferences used in assessments. We encourage broad community participation toward the expansion and ongoing development of the proposed standards and guidelines.

Subfields: Ecological Modeling, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/3a04bf110e5a84e856633ac35d18bb50761be572

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In Ecological Modeling

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

A standard protocol for reporting species distribution models (2020, methodology): “Nesting accounts for the fact that transfer should not be attempted without first having a thorough understanding of the model (inference) (Araújo et al. 2019).”
ENMeval 2.0: Redesigned for customizable and reproducible modeling of species’ niches and distributions (2021, methodology): “This framework is the basis for a recently proposed stand - ardized protocol for reporting on ENMs (Zurell et al., 2020), fol - lowing comprehensive reproducibility standards (Feng et al., 2019) and facilitating the assessment of model adequacy for applied uses (Araújo et al., 2019).”
Testing species assemblage predictions from stacked and joint species distribution models (2019, methodology): “Following current stan‐ dards (Araújo et al., 2019), SDMs and MEMs were fitted using an ensemble approach with four different algorithms: generalized lin‐ ear models (GLM), generalized additive models (GAM), boosted re‐ gression trees (BRT) and random forests (RF) with a binomial error distribution…”
Insect responses to global change offer signposts for biodiversity and conservation (2020, methodology): “Theory, experiments and modelling have been widely used to predict how biodiversity will respond to global climate change (Kerr et al., 2007; De Boeck et al., 2015; Titeux et al., 2017; Araújo et al., 2019).”